14 November 2026, Columbia, US: Researchers at the University of Missouri have created rice plants that fight off bacterial blight, one of the most damaging diseases affecting the world’s most widely grown staple crop, by adapting an artificial-intelligence-designed gene-editing tool that had previously only been used in animal cells.
The work was led by Bing Yang, a Curators’ Distinguished Professor in the University of Missouri’s College of Agriculture, Food and Natural Resources and an investigator at the university’s Bond Life Sciences Center. Yang and colleagues, including Ajay Gupta, Rabia Ahuja and Bo Liu, described the research in the journal aBIOTECH.
Bacterial blight, caused by the bacterium Xanthomonas oryzae, is considered one of the most destructive rice diseases worldwide and has been shown in past outbreaks to cut yields by as much as 70 percent in severely affected fields. Because rice is a dietary staple for more than half the world’s population, plant pathologists have spent decades searching for durable ways to protect the crop from the pathogen without relying solely on chemical controls.
From animal cells to rice paddies
The breakthrough centers on OpenCRISPR-1, a gene-editing system originally developed by the California biotechnology company Profluent using artificial intelligence to design its molecular components. Profluent had previously demonstrated the tool’s effectiveness in animal cells, but Yang’s team adapted the system for use in plants, applying it to rice for what the university describes as the first time.
Unlike earlier gene-editing approaches to disease resistance, which have often targeted specific resistance genes or the promoter regions that control them, the AI-designed nature of OpenCRISPR-1 is intended to make the editing process more precise and potentially faster to apply across different genetic backgrounds. The University of Missouri team’s approach builds on more than a decade of work in Yang’s lab studying how Xanthomonas oryzae infects rice plants and how the plant’s own genome can be altered to block that process.
The university has not released specific figures on how much the edited rice lines’ disease resistance improved in laboratory trials, nor has it disclosed a funding source for the current study. It also cautioned that the modified rice remains a laboratory line rather than a crop ready for farmers’ fields. Moving the trait from that laboratory line into rice varieties already grown commercially, and through the regulatory and breeding processes required before any seed reaches growers, is expected to take several more years, according to the university.
Why blight keeps coming back
Bacterial blight has proven especially difficult to manage because the Xanthomonas oryzae bacterium can evolve to overcome individual resistance genes bred into rice varieties, forcing breeders to continually search for new sources of resistance. Gene-editing tools that allow researchers to make precise, targeted changes to a plant’s own DNA, without introducing foreign genetic material, have emerged over the past several years as one avenue for addressing that problem more quickly than conventional breeding alone.
Yang’s laboratory has worked on rice disease resistance for years in collaboration with institutions including the Donald Danforth Plant Science Center, and the lab’s earlier work using older CRISPR tools to edit the promoter regions of susceptibility genes in rice was previously recognized by regulators in the United States and Colombia as equivalent to conventional breeding, clearing a path for field testing of those separate, earlier lines. The new OpenCRISPR-1 work represents a more recent application of gene-editing technology to the same underlying disease problem facing rice growers, this time using a tool whose components were generated by artificial intelligence rather than adapted from naturally occurring bacterial systems.
Most CRISPR systems used in agricultural research to date have been derived from naturally occurring bacterial immune defenses, discovered and then adapted by scientists for use in editing plant and animal genomes. OpenCRISPR-1 took a different route, with Profluent using machine learning models trained on large numbers of known CRISPR proteins to generate new, synthetic editing components that do not occur in nature but are designed to perform the same cutting and editing functions. Yang’s group is among the first to test whether an AI-generated editing system of this kind can be deployed effectively in a crop plant rather than in laboratory animal cells, where the tool was first validated.
The university has not said whether the edited rice lines described in the aBIOTECH paper have been tested against multiple strains of Xanthomonas oryzae, which can vary significantly by region, or whether field trials outside a controlled laboratory setting are currently planned. For rice-growing regions across Asia, Africa and Latin America, where bacterial blight remains a persistent constraint on yields, any new source of durable resistance is likely to draw interest from national breeding programs once further data on the trait’s performance and stability becomes available.
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